Mining Intention-Related Products on Online Q&A Community

User generated content on social media has attracted much attention from service/product providers, as it contains plenty of potential commercial opportunities. However, previous work mainly focuses on user Consumption Intention (CI) identification, and little effort has been spent to mine intention-related products. In this paper, we propose a novel approach to mine intention-related products on online Question & Answer (Q&A) community. Making use of the question-answer pairs as data source, we first automatically extract candidate products based on dependency parser. And then by means of the collocation extraction model, we identify the real intention-related products from the candidate set. The experimental results on our carefully constructed evaluation dataset show that our approach achieves better performance than two natural baseline methods. Our method is general enough for domain adaptation.